Chief Architect – Data Engineering (Databricks Practice)

About the role

We are expanding our Databricks practice in APAC and need a senior technical leader to own end‑to‑end data engineering solutions. As Chief Architect you will drive architecture, delivery and presales for enterprise‑scale Databricks platforms while mentoring the team.

Key responsibilities

• Define and own architecture and design for Databricks engagements, ensuring security, scalability and performance.
• Lead delivery of production‑grade data platforms covering ingestion, transformation, orchestration, governance (Unity Catalog) and downstream BI/ML enablement.
• Manage large‑scale migrations from legacy DW/ETL, Hadoop or on‑prem environments to Databricks on Azure, AWS or GCP.
• Participate hands‑on in performance tuning, debugging, code reviews and setting engineering standards.
• Present and defend solution designs to architecture boards, CIOs and CTOs and drive presales activities including discovery, PoCs, estimations and proposals.
• Mentor engineers, create reusable accelerators and translate delivery success into case studies and go‑to‑market assets.

Required profile

• 12+ years of data engineering/architecture experience, with at least 3 years on Databricks at enterprise scale.
• Deep expertise in Apache Spark (architecture, performance tuning, streaming).
• Proven track record of leading complex migration and cloud transformation programs.
• Strong presales instincts – able to design, price and defend solutions to senior executives.
• Hands‑on coder who enjoys working directly with data pipelines.

Required skills

• Databricks, Azure, AWS, GCP
• Apache Spark, Python, SQL, Scala
• Lakehouse concepts: Medallion architecture, Delta Lake, Unity Catalog
• Orchestration tools: Databricks Workflows, DLT/Lakeflow, Airflow, Azure Data Factory
• CI/CD for data platforms
• MLflow, LLM APIs (OpenAI, Anthropic)